From a group of 60 patients with dentoalveolar infections among which 10 were diabetic and 10 non-diabetic were elected as test group as well as 10 normal subjects as control group. Six Staphylococcus aureus and Streptococcus anginousus were diagnosed in the first and second group of the patients the immune status of the patients and control subject were tested by pathogen specific antibody titre, neotrophil NBT reduction phagocytosis and leukocyte inhibition LIF. Diabetic patients with dentoalveolar infection shows decreased specific antibody titers, subnormal neutrophil NBT phagocytic % as well as non significant LIF % in comparison non diabetic reveal high specific antibody titers against , high neutrophil NBT% and significant LIF% respectively thus diabetic indicate humoral and cellular immune suppression along the den to alveolar infection.
In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.
The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreToday, more than ever before, the business organizations’ initiatives should seek to design themselves and delivery them to the environment because of its change, and the increasing of uncertainties and the growing opportunities. What is required by the business organizations is that to adopt good approaches to stimulate the modern thinking and non traditional thinking and exploit the valued concepts and overcome the old thinking. Substantially, the scenario planning is the art of thinking about what is unexpected.
Therefore the research’s problem is reflected to answer the following questions:
- What
Fibroblast growth factor-23, play an important role in atherosclerosis, endothelial dysfunction and vascular calcification. Sevelamer can improve vascular calcification, serum uric acid, low-density lipoprotein-cholesterol and Fibroblast growth factor-23. Aim of study Assessment the effect of sevelamer as phosphate binder against calcium carbonate on Fibroblast growth factor-23. Methods A prospective open-labelled study that included patients on hemodialysis. A total of 72 patients were screened, only 53 patients completed the 10 week period. Adults patients with serum phosphate as> 5.5 mg/dl were included. There were Group1: Includes 28 patients (19 males and 9 females receiving sevelamer carbonate (Renvela) tablet. Group 2: Include 25pati
... Show MoreAbstract Objectives: to determine efficiency and safety of three misoprostol regimens for 2nd trimester pregnancy termination in individuals with two or more cesarean section scars. Methods: a cross-sectional study included 100 pregnant ladies at 13th-26th weeks gestation with previous two cesarean sections (CSs) who were scheduled for pregnancy termination using misoprostol. Patients were conveniently assigned to 100µg/3h, 200µg/3h or 400 µg/3h regimens. Primary outcome was time to abortion, secondary outcomes were side effect and complications. Results: a significant association was found between number previous CSs and longer time to abortion (p=0.01). A highly significant association was identified between earlier gestatio
... Show MoreObjectives The gold standard in the field of periodontal research currently is to find a valid biomarker that can reliably be used for diagnosing periodontal diseases. Given the limitations of the current diagnostic tools that stall to predict susceptible individuals and determine whether active tissue destruction is occurring, there is an increased urge to develop alternative diagnostic techniques that would compensate for the problems inherited in these available methods, such as measuring levels of biomarkers present in oral fluids such as saliva; so the aim of this study was to determine the diagnostic potential of interleukin-17 (IL-17) and IL-10 to differentiate periodontal health
Background: Recent studies suggest that chronic periodontitis (CP) and type2 diabetes mellitus (T2DM) are bidirectionally associated. Analysis of saliva as a mirror of oral and systemic health could allow identification of α amylase (α-Am) and albumin (A1) antioxidant system markers to assist in the diagnosis and monitoring of both diseases. The present study aims at comparing the clinical periodontal parameters in chronic periodontitis patients with poorly or well controlled Type 2Diabetes Mellitus, salivary α-Am, A1, flow rate (FR) and pH then correlate between biochemical, physical and clinical periodontal parameters of each study and control groups. Materials and Methods: 80 males, with an age range of (35-50) years were divide
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